This invention relates generally to systems and methods for operating a mass flow controller (MFC) with a closed loop control system utilizing an advanced digital control algorithm. More specifically, the present invention provides a closed loop control system for operating a mass flow controller, wherein all mathematical operators are realized within a digital processor.
Many manufacturing processes require that the introduction rates of process gases into a process chamber be strictly controlled. These types of processes use mass flow controllers (MFCs) to control the flow rate of gases. Many problems exist with current technology mass flow controllers.
MFC""s have a high cost of ownership due to unscheduled maintenance of the tools in which the MFC are installed. Often there is no indication as to a specific type of failure. Common practice is to replace the MFC since it is perceived as a dynamic device that is believed to be inherently unreliable. As a result, a significant number of MFC""s are returned to the factory and found to operate as specified resulting in a no problem found failure analysis.
The lack of internal diagnostics or the ability to provide remote service of the MFC and remote diagnostics necessitates that a well trained field service engineer or application engineer must visit the customer site to provide on-site tech support and failure analysis once an MFC has been installed. Another shortcoming is that the individual device performance, specifically accuracy and response time or transient performance, is dependent upon a time-consuming, labor-intensive, manual calibration and tuning process, using potentiometers or variable resistors.
Today, the manufacturing process is a highly manual process requiring that a technician use several devices such as oscilloscopes, different secondary flow measurement devices, and the like and visual inspections of those other devices to determine certain signals and tunes the potentiometers to his satisfaction.
This creates a set of devices that are dependent upon the personnel that tune the devices. The devices are commonly non-uniform and not repeatable from one unit to the other creating complex process engineering and characterization problems so each device has its own unique behavior associated with the device. MFC behavior is directly a function of the manual tuning process and the technician that performs the process. Additionally, the transit response of traditional mass flow controllers are not uniform. The performance from, for example, 0 or 10% of set point is different from 0-100%. This varying response creates a problem for the process control engineers that depend on these devices. The unique response of an individual device forces engineers to uniquely characterize MFC device behavior to account for the variability and the response times depending upon certain situations. This characterization process is both expensive and time consuming.
Current MFC""s are sensitive to inlet pressure. The mass flow controller requires a certain inlet pressure specification and the differential pressure is normally specified to be approximately 45 PSID so the performance of existing MFC devices are typically optimized as to one specific pressure. Trade-offs are made when the inlet pressure is varied over a particular pressure range, which creates more variability of the response time and characterization of a device.
One solution to inlet pressure sensitivity requires that the user install often expensive pressure regulators.
In the gas lines that supply the gas to the MFC it would be advantageous to have a mass flow controller that is not sensitive to pressure fluctuations in order that expensive pressure regulation hardware can be removed. Furthermore, each device has a pressure transducer adjacent to the pressure regulator which sole purpose is to indicate that the pressure regulator is functioning.
Furthermore, there is a need to comply with emerging standards open communication standards and instrumentation. EIARS485 is an open standard for multi-drop but it only describes the physical layer. So the software protocol stack is subject proprietary implementations from one supplier to another. So it is desirable to have mass flow controllers that have high performance communications service ability that implement open protocols while not sacrificing flow control parameters.
A powerful solution to understanding unknown or poorly understood processes is to learn of the process through regression analysis. Regression analysis is a structured approach utilizing carefully designed experiments to optimize multivariable engineering processes. This technique allows a process to be understood and potentially exploited through a series of experiments. The usual method of estimation for the regression model is ordinary least squares (OLS).
Regression analysis also allows the creation of diagnostic procedures that compare the predicted values to actual values to evaluate the performance of the regression estimates through the use of residuals.
The overall task is to provide the best flow control performance possible while not sacrificing other issues such as communications, multiple gas calibrations and cost of ownership.
The present invention provides a system and method for operating a mass flow controller that substantially eliminates or reduces disadvantages and problems associated with previously developed systems and methods for operating a mass flow controller.
The chosen architecture of the present invention does not sacrifice to flow control for the ability to service a communications network.
The present invention provides embedded diagnostics within the chosen architecture or system. Specifically, the digital engine of the present invention will discretely monitor system variables. These variables include but are not limited to the flow set-point, solenoid current, ambient temperature, the resistance of the flow sensor, and the inlet pressure which may be measured by an external pressure transducer. Several of these variables are a valuable source of information to monitor and to reduce MFC pressure sensitivity. The digital engine also will monitor power supply voltages.
The internal digital mass flow controller embedded system architecture is specifically intended to improve the performance of an MFC over prior art systems and adds several value-added features.
The mass flow controller of the present invention does not contain any variable manual adjustments. This provides an advantage in that all calibration and tuning is completed digitally via storage of a unique set of constants stored in nonvolatile memory. Access to the relevant memory locations is provided via the dedicated RS485 interface. The calibration system host, running the appropriate software and interfacing to specific flow measuring instrumentation, can automatically calibrate and tune the mass flow controller of the present invention for uniform repeatable performance in static and transient flow conditions. These uniform transient responses provide an addition advantage of the present invention. These uniform transient responses are achieved by using the computational power provided by the selected digital signal processor as applied in the chosen architecture. This architecture allows 100% of the control algorithms to be implemented via software. The software algorithms can contain mechanisms to invoke unique case-sensitive or situational parameters that can be selected or tuned to achieve a uniform and repeatable transient response.
In certain embodiments, these methods of calibrating a mass flow controller include the steps of measuring the real time actual flow through the mass flow controller with a flow measuring instrumentation system; and sensing a series of system variables associated with a mass flow controller wherein the variables comprise: a desired output flow setpoint, a solenoid current, an ambient temperature, a base resistance of the sensor, an inlet pressure indication, at least one power supply voltage, a leakage through the control valve, and real time flow error between an actual output flow as compared to the desired output flow set-point. These methods may also include modeling a predicted flow through the mass flow controller with a regression analysis technique to produce a multivariable response function describing a response of the mass flow controller to the system variables; and inputting the multivariable response function into an electronic control system operable to regulate the flow through the mass flow controller.
In other embodiments the multivariable response function may be archived in a memory location within the electronic control system.
Yet another advantage of the present invention is to eliminate the need for expensive upstream pressure regulators within a gas supply. The digital engine of the present invention has the capability to discretely monitor the inlet pressure via an available A/D input. It is desirable to monitor the input pressure and desensitize the mass flow characteristics of the output of the present invention.
A further advantage of the present invention is that it can contain multiple autonomous dedicated digital communication ports. This architecture allows multiple digital networks to be serviced simultaneously. Specific embodiments of the present invention provide that one network is an RS485 type network. The chosen DSP includes an embedded UART peripheral that is dedicated to service RS485 networks. An additional communication network can be serviced via reading and writing to a dual-port SRAM. The selection of the dual-port SRAM as a communication partition enables the support of autonomous interchangeable interfaces. The present invention should not be necessarily limited to these two communication ports. Multiple communication ports of various communication protocols as known to those skilled in the art can be incorporated into the present invention to achieve autonomous interchangeable interfaces.
An additional advantage of the present invention is that the embedded system manages events based upon receiving sample data from the flow signal at precise discrete intervals of 1.68 milliseconds. Due to the computational power of the chosen architecture, the control""s algorithm completes its task in less than 30% of this time.